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The neurocognitive performance of drug‐free and medicated euthymic bipolar patients do not differ

2009· article· en· W1998911276 on OpenAlexaff
Utpal Goswami, Aditya Sharma, Amit H. Varma, Chinmoy Gulrajani, I. N. Ferrier, Allan H. Young, Peter Gallagher, J. M. Thompson, P. Brian Moore

Bibliographic record

VenueActa Psychiatrica Scandinavica · 2009
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsUniversity of British Columbia
FundersUniversity Grants CommissionRoyal SocietyIndian National Science Academy
KeywordsNeurocognitivePerseverationMoodNeuropsychologyVerbal memoryVerbal learningBipolar disorderPsychologyPsychiatryDepression (economics)Neuropsychological testCognitionEffects of sleep deprivation on cognitive performanceDonepezilDementiaClinical psychologyMedicineInternal medicineDisease

Abstract

fetched live from OpenAlex

OBJECTIVE: Although it is established that euthymic bipolar patients have neurocognitive deficits, the influence of medication on their cognitive performance is uncertain and requires investigation. METHOD: Neuropsychological tests of executive function, memory and attention were performed on 44 prospectively verified, euthymic bipolar I patients, 22 of whom were drug-free. Residual mood symptom effects were controlled statistically using ancova. RESULTS: Drug-free and medicated patients differed only in delayed verbal recall (Rey AVLT list A7, drug-free > medicated), and perseverations during the five-point test (drug-free > medicated). When residual mood symptoms were controlled statistically, differences between drug-free and medicated subjects became insignificant. Medication effect sizes were modest. Significant correlations were found between residual depression scores and measures of verbal learning. CONCLUSION: Medications did not have any significant influence on neurocognitive performance, suggesting that neurocognitive deficits are an integral part of bipolar disorder.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.569

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.233
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations74
Published2009
Admission routes1
Has abstractyes

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Same venueActa Psychiatrica ScandinavicaSame topicBipolar Disorder and TreatmentFrench-language works237,207